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* docs(cli): document device-code login and config reset guidance; renumber sections * docs(cli): fix duplicate numbering (renumber Login/API Keys/Configuration sections) * docs: Fix webhook documentation to include meta dict in all webhook payloads - Add note explaining that meta objects from kickoff requests are included in all webhook payloads - Update webhook examples to show proper payload structure including meta field - Fix webhook examples to match actual API implementation - Apply changes to English, Korean, and Portuguese documentation Resolves the documentation gap where meta dict passing to webhooks was not documented despite being implemented in the API. * WIP: CrewAI docs theme, changelog, GEO, localization * docs(cli): fix merge markers; ensure mode: "wide"; convert ASCII tables to Markdown (en/pt-BR/ko) * docs: add group icons across locales; split Automation/Integrations; update tools overviews and links
74 lines
2.5 KiB
Plaintext
74 lines
2.5 KiB
Plaintext
---
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title: MDX RAG Search
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description: The `MDXSearchTool` is designed to search MDX files and return the most relevant results.
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icon: markdown
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mode: "wide"
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---
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# `MDXSearchTool`
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<Note>
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The MDXSearchTool is in continuous development. Features may be added or removed, and functionality could change unpredictably as we refine the tool.
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</Note>
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## Description
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The MDX Search Tool is a component of the `crewai_tools` package aimed at facilitating advanced markdown language extraction. It enables users to effectively search and extract relevant information from MD files using query-based searches. This tool is invaluable for data analysis, information management, and research tasks, streamlining the process of finding specific information within large document collections.
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## Installation
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Before using the MDX Search Tool, ensure the `crewai_tools` package is installed. If it is not, you can install it with the following command:
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```shell
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pip install 'crewai[tools]'
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```
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## Usage Example
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To use the MDX Search Tool, you must first set up the necessary environment variables. Then, integrate the tool into your crewAI project to begin your market research. Below is a basic example of how to do this:
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```python Code
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from crewai_tools import MDXSearchTool
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# Initialize the tool to search any MDX content it learns about during execution
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tool = MDXSearchTool()
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# OR
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# Initialize the tool with a specific MDX file path for an exclusive search within that document
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tool = MDXSearchTool(mdx='path/to/your/document.mdx')
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```
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## Parameters
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- mdx: **Optional**. Specifies the MDX file path for the search. It can be provided during initialization.
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## Customization of Model and Embeddings
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The tool defaults to using OpenAI for embeddings and summarization. For customization, utilize a configuration dictionary as shown below:
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```python Code
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tool = MDXSearchTool(
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config=dict(
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llm=dict(
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provider="ollama", # Options include google, openai, anthropic, llama2, etc.
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config=dict(
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model="llama2",
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# Optional parameters can be included here.
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# temperature=0.5,
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# top_p=1,
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# stream=true,
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),
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),
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embedder=dict(
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provider="google", # or openai, ollama, ...
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config=dict(
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model="models/embedding-001",
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task_type="retrieval_document",
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# Optional title for the embeddings can be added here.
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# title="Embeddings",
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),
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),
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)
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)
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``` |